In information systems, most research on knowledge management assumes that knowledge has positive implications for organizations. However, knowledge is a double-edged sword: while too little might result in expensive mistakes, too much might result in unwanted accountability. The purpose of this paper is to highlight the lack of attention paid to the unintended consequences of managing organizational knowledge and thereby to broaden the scope of IS-based knowledge management research. To this end, this paper analyzes the IS literature on knowledge management. Using a framework developed by Deetz (1996), research articles published between 1990 and 2000 in six IS journals are classified into one of four scientific discourses. These discourses are the normative, the interpretive, the critical, and the dialogic. For each of these discourses, we identify the research focus, the metaphors of knowledge, the theoretical foundations, and the implications apparent in the articles representing it. The metaphors of knowledge that emerge from this analysis are knowledge as object, asset, mind, commodity, and discipline. Furthermore, we present a paper that is exemplary of each discourse. Our objective with this analysis is to raise IS researchers' awareness of the potential and the implications of the different discourses in the study of knowledge and knowledge management.

Studying knowledge management in information systems research: discourses and theoretical assumptions

Limitations in healthcare funding require hospitals to find more effective ways to utilize resources. An effective patient management system is critically dependent on the accurate analysis of individual patient outcomes and resource utilization. In the current paper, a management-oriented decision support model is thus proposed to assist health system managers in improving the efficiency of their systems. In the first stage of the model, the key variables affecting system efficiency, as well as their causal relationships, are identified through causal maps. Efficiency is measured by the total time spent in the system. In the second stage, a Bayesian Belief Network (BBN) is employed to represent both the conditional dependencies and uncertainties of the key variables. In the third stage, a sensitivity analysis is performed using a BBN to determine the most critical variable(s) in terms of impact on the system. Finally, strategies to improve system efficiency are proposed. The suggested decision support system is applied to the tomography section in the radiology department of a private hospital in Turkey.

A decision support system to improve the efficiency of resource allocation in healthcare management

Policy developments for the reduction of climate change impacts by the transportation sector

Bibliometric maps of science are a well-established research subject. But their adoption as a science policy support tool is lacking. We think this is because the user does not immediately comprehend a map and (as a result) is not enticed into using it. To help this comprehension, we propose the use of “qualitative maps”: an umbrella term for diverse tools such as concept maps and mental maps. We developed a tool that interfaces between a qualitative map and a bibliometric map which lets the user create a correspondence between the distinct vocabularies of the maps. We also conducted two user studies: the first explored the combined use of bibliometric and qualitative maps and the second the preferred format of the map and the word-usage in the description of its elements.

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Combining concept maps and bibliometric maps: First explorations

The important contemporary issue of VLSI design verification is its time-consuming. The hardware model, written, for instance, with VHDL, is verified by formal and dynamic verification approaches. Dynamic verification (simulation) is widely-used due to the possibility of full automation of the process, but takes too much time due to its redundancy.

B. Shekar

Papers

Applications of uncertainty-based mental models in organizational learning: A case study in the Indian automobile industry